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xAI new grad / entry level interview: how to prep when there's barely any info online

pivot_pat · 5 replies

ok so i'm a 2025 grad and i got a recruiter reach-out from xAI last month. panicked immediately because there's almost nothing online about what the new grad loop looks like. ended up getting pretty far (made it past the phone screen, no offer in the end) and i want to post what i found so the next person has something to work with.

what i could piece together going in xAI is small, moves fast, and doesn't have a structured new grad program the way Meta or Google do. there's no rotational thing, no dedicated new grad onboarding cohort. you're expected to get productive quickly. this matters for prep because you're not just showing you can do CS fundamentals, you're showing you can own work.

phone screen standard coding question. i got a medium-difficulty graph traversal problem. had to find shortest path with weighted edges and some additional constraints i won't give away exactly. they were watching how i talked through my approach before coding, not just whether i got it. i spent the first 5 minutes walking through examples and edge cases before writing a line of code. that felt right in hindsight.

what i heard from the recruiter about the onsite (i didn't get there) she said it's typically 4 rounds: two coding, one system design (simplified for new grad level), one behavioral. the system design prompt for new grads is supposedly scoped to something like 'design a URL shortener' or similar canonical problems. you want to know the basics: storage estimation, read/write paths, caching, basic scalability.

what i'd prep if i could do it over drill leetcode medium graph, DP, and string problems. not hard, but consistently medium. practice talking out loud while coding. this is actually harder than the coding. read up on distributed systems basics even for new grad. you don't need staff-level depth but you should know what a load balancer does and why you'd cache something. have one or two real stories about projects. not classroom projects if possible. internship work, personal projects with real users, open source contributions.

things specific to xAI as a company they're building Grok and associated infra. if you have any background in LLM inference, training pipelines, or even just know the terminology around transformer architecture, mention it. they're not going to quiz a new grad on it but it signals you're paying attention to what they're actually building.

anybody who's been further in the new grad loop, please drop what you saw. i'm trying to help build out this data.

5 replies

jordan_pm

thanks for posting this. the 'talk out loud while coding' thing is real and something schools just don't prepare you for at all. i bombed my first two phone screens because i was coding silently and then explaining after. it reads as not knowing what you're doing even when you do.

consultant_cam

the point about new grad loops at small AI companies vs big tech is worth emphasizing. at Google/Meta there's a whole machine to onboard and ramp you. at a 500-person company like xAI you might be the first engineer on a sub-team. they're calibrating for self-direction, not just technical chops. behavioral stories where YOU drove something matter a lot more than people expect.

alex_design

one more thing i forgot: the recruiter mentioned they look at github and any public technical writing you have. not required but if you have it, make sure it's linked on your resume. first impression is set before you get on the call.

bootcamp_bri

do they consider bootcamp grads or is it strictly cs degree? asking because i'm in a similar position looking at AI startup interviews.

ux_uma

i honestly don't know. my recruiter was from linkedin outreach so i had a cs degree on my profile. i'd assume the coding screen is the real filter regardless of background, but i can't say for sure on the bootcamp question. worth applying to find out.